The present invention relates to estimating properties of three-dimensional (3D) objects in two-dimensional (2D) video data.
Understanding and determining the import of the various object movements, for example a person approaching an area or taking some sort of action that exposes that person or others to a heightened hazard risk, may be difficult from 2D video data streams. Human operators may be required to simultaneously review and analyze multiple monitors or display windows for object movements, and the 2D nature of video data may make object recognition and tracking by the human eye difficult, particularly in visually rich or noisy environments.
Object tracking and recognition may be improved when 2D video data objects are modeled with 3D models, in one aspect as recognizing and tracking 3D objects is inherently more intuitive to human observers. However, adequately rendering such 3D models with regard to moving objects is a complex process, generally requiring complex data processing and/or data inputs from other cameras or other devices, such as range, image and/or object tracking sensors, making robust modeling difficult to achieve.